期刊
JOURNAL OF EPIDEMIOLOGY AND COMMUNITY HEALTH
卷 75, 期 8, 页码 749-754出版社
BMJ PUBLISHING GROUP
DOI: 10.1136/jech-2020-215539
关键词
ageing; cardiovascular disease; cohort studies; health behaviour; social factors in
资金
- National Institute on Aging [R01AG017644]
- Wellcome Trust [205407/Z/16/Z]
- Leverhulme Trust [PLP-2018-007]
This study identified latent clustering of cardiovascular risk factors among adults aged 50+, showing how risk factors cluster together and how the risk patterns are related to social factors. Loneliness was found to be associated with a higher risk of certain classes, while social disengagement and living alone were also differentially associated with latent class memberships. The findings offer important implications for clinical practice and preventive interventions in cardiovascular disease.
Background There is growing research into the effects of psychological and social factors such as loneliness and isolation on cardiovascular disease (CVD). However, it is unclear whether individuals with particular clusters of CVD risk factors are more strongly affected by loneliness and isolation. This study aimed to identify latent clustering of modifiable risk factors among adults aged 50+ and explore the relationship between loneliness, social isolation and risk factor patterns. Methods Data from 8218 adults of English Longitudinal Study of Ageing were used in latent class analyses to identify latent classes of cardiovascular risk factors and predictors of class membership. Results There were four latent classes: low-risk (30.2%), high-risk (15.0%), clinical-risk (42.6%) and lifestyle-risk (12.2%) classes. Loneliness was associated with a greater risk of being in the high-risk class (relative risk ratio (RRR) 2.40, 95% CI 2.40 to 1.96) and lifestyle-risk class (RRR 1.36, 95% CI 1.10 to 1.67) and a lower risk of being in the clinical-risk class (RRR 0.84, 95% CI 0.72 to 0.98) relative to the low-risk class. Social disengagement, living alone and low social contact were also differentially associated with latent class memberships. Conclusion These findings supplement our existing knowledge of modifiable risk factors for CVD by showing how risk factors cluster together and how the risk patterns are related to social factors, offering important implications for clinical practice and preventive interventions.
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